GA Implementation Path Optimization of Pneumatic Marking System

2013 ◽  
Vol 391 ◽  
pp. 390-393
Author(s):  
Lei Shao ◽  
Hai Bin Zuo ◽  
Nan Liu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Path Optimization ◽  
Matlab Simulation

According to the characteristics of pneumatic marking system, and the typing path was seen as a TSP problem. After comparing the Dijkstra optimization algorithm of marking path results, and applying the genetic algorithm (GA) to analysis, research, and solve the optimization problem, reasonable to get print needle typing path. In this case, printing mark time was shorten as much as possible. It was proved by MATLAB simulation that the study can solve the problem of path optimization and improve the efficiency of marking greatly.

Artificial Life Optimization Algorithm and Applications

2011 ◽  
pp. 423-449
Author(s):  
Bo-Suk Yang
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Artificial Life ◽  
Optimization Problem ◽  
Global Optimum ◽  
Function Optimization ◽  
Global Function ◽  
Test Function ◽  
Optimum Solution ◽  
Artificial World

This chapter describes a hybrid artificial life optimization algorithm (ALRT) based on emergent colonization to compute the solutions of global function optimization problem. In the ALRT, the emergent colony is a fundamental mechanism to search the optimum solution and can be accomplished through the metabolism, movement and reproduction among artificial organisms which appear at the optimum locations in the artificial world. In this case, the optimum locations mean the optimum solutions in the optimization problem. Hence, the ALRT focuses on the searching for the optimum solution in the location of emergent colonies and can achieve more accurate global optimum. The optimization results using different types of test functions are presented to demonstrate the described approach successfully achieves optimum performance. The algorithm is also applied to the test function optimization and optimum design of short journal bearing as a practical application. The optimized results are compared with those of genetic algorithm and successive quadratic programming to identify the optimizing ability.

scholarly journals Research on the Path Optimization Problem of Multi-Centre Distribution System

2018 ◽  
Vol 232 ◽  
pp. 04034
Author(s):  
Kai-lun HE ◽  
Yi DING ◽  
Hui-long SUN
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Optimization Problem ◽  
Path Optimization ◽  
Routing Problem ◽  
Actual Environment ◽  
Distribution Cost

Based on the actual environment, the routing problem of multi centre distribution system is theoretically described and analyzed, and a genetic algorithm for solving the problem is proposed and verified by an example. The research shows that the genetic algorithm can be used effectively to optimize the distribution path and reduce the distribution cost. At the same time, the program is easy to operate and is convenient for the enterprise to apply.

Based on Genetic Algorithm Research of Stocker Picking Shortest Path

2012 ◽  
Vol 155-156 ◽  
pp. 186-190
Author(s):  
Fu Cai Wan ◽  
Duo Chen ◽  
Yong Qiang Wu
Keyword(s):  
Genetic Algorithm ◽  
Shortest Path ◽  
Optimization Problem ◽  
Traveling Salesman ◽  
Path Optimization ◽  
Improved Genetic Algorithm ◽  
Operating Process ◽  
Path Distance ◽  
Simulation Results ◽  
The Mathematical Model

This paper analyzes characteristics of automated warehouse stocker picking operating process. Path optimization problem is considered as traveling salesman problem. The coordinates of picking points by calculating determine a stocker running route. The mathematical model of a path distance is built. And using the improved genetic algorithm solves the above problem. Finally, M-file program of stocker running path optimization is written and run in MATLAB. The simulation results that, in solving stocker path optimization problem, it can search for a shortest path by genetic algorithm. Thereby enhance the efficiency of automated warehouse system, increase greater benefits of the enterprise.

Hybrid IWD-GA: An Approach for Path Optimization and Control of Multiple Mobile Robot in Obscure Static and Dynamic Environments

Robotica ◽  
2021 ◽  
pp. 1-28
Author(s):  
Saroj Kumar ◽  
Dayal Ramakrushna Parhi ◽  
Krishna Kant Pandey ◽  
Manoj Kumar Muni
Keyword(s):  
Genetic Algorithm ◽  
Path Length ◽  
Water Drop ◽  
Optimal Path ◽  
Dynamic Environments ◽  
Path Optimization ◽  
Matlab Simulation ◽  
Optimization And Control ◽  
Global Optimal ◽  
And Control

SUMMARY In this article, hybridization of IWD (intelligent water drop) and GA (genetic algorithm) technique is developed and executed in order to obtain global optimal path by replacing local optimal points. Sensors of mobile robots are used for mapping and detecting the environment and obstacles present. The developed technique is tested in MATLAB simulation platform, and experimental analysis is performed in real-time environments to observe the effectiveness of IWD-GA technique. Furthermore, statistical analysis of obtained results is also performed for testing their linearity and normality. A significant improvement of about 13.14% in terms of path length is reported when the proposed technique is tested against other existing techniques.

Perceptive Exploration of Layout Designs Using an Interactive Genetic Algorithm

2012 ◽  
Author(s):  
Julien Bénabès ◽  
Emilie Poirson ◽  
Fouad Bennis ◽  
Yannick Ravaut
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Subjective Evaluation ◽  
Performance Criteria ◽  
Final Decision ◽  
Complex Task ◽  
Optimal Layout ◽  
Interactive Genetic Algorithm ◽  
Qualitative Performance

Layout design optimization has a significant impact in the design and use of many engineering products and systems, such as the subdivision of a ship, the layout of facilities in a plant or further still the assembly of parts of a mechanism. The search for an optimal layout configuration is a critical and complex task due to the increasing demands of designers working on varied projects. A layout optimization process is generally divided into different steps: the description, formulation and solving of the problem and the final decision. This process consists in writing an optimization problem that transform designer’s requirements into variables, constraints and objectives. Then, an optimization algorithm has to be used in order to search for optimal solutions that fit with product’s specifications. This paper focuses on the last step which consists, for the designer, in making a choice on the solutions generated by the optimization algorithm. This choice is made according to the global performances of the designs and also the personal judgment of the designer. This judgment is based on the expertise of the designer and the subjective requirements that could not be integrated on the formulation of the problem. This paper proposes a perceptive exploration method, based on an Interactive Genetic Algorithm (IGA), used to explore designs, taking into account the subjective evaluation of the designer. The objective of this method is to select an ideal solution that realizes the best trade-off between the quantitative and qualitative performance criteria. This interactive process is tested on an industrial layout application which deals with the search for an optimal layout of facilities in a shelter.

Method of Holes Machining Path Optimization for NC Turret Punch Press

2013 ◽  
Vol 842 ◽  
pp. 553-557
Author(s):  
Pei Si Zhong ◽  
Ying Jing Yu ◽  
Hai Liang Xin ◽  
Zhen Guo Lu
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Optimization Algorithm ◽  
Optimization Methods ◽  
Path Optimization ◽  
Distance Method ◽  
Basic Composition ◽  
Different Types ◽  
Working Principle ◽  
Punch Press

The basic composition and working principle of the turret punch press were analyzed, the recent distance method and genetic algorithm optimize method of holes machining path of NC turret punch press was put forward, the corresponding mathematical model and optimization algorithm was respectively given, these two kinds of optimization methods aiming at different types of holes are compared with the examples, put forward a kind of the integrated holes machining path optimization.

Route Optimization of DGT Based on Improved Genetic Algorithm

2014 ◽  
Vol 536-537 ◽  
pp. 845-848
Author(s):  
Tong Jie Zhang ◽  
Yan Cao ◽  
Xiang Wei Mu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Route Optimization ◽  
Path Optimization ◽  
Initial Population ◽  
Local Optimum ◽  
Search Efficiency ◽  
Improved Genetic Algorithm ◽  
Adaptive Adjustment ◽  
Dynamic Operator

An improved genetic algorithm for route optimization in DGT is proposed in this paper. In which, method of initial population, cross and mutation are improved to make it more suitable for DGT. It uses a dynamic operator to realize the adaptive adjustment of the parameters. The experimental results show that the improved algorithm overcomes the shortcomings of local optimum and "premature convergence" and improves the search efficiency and adaptability. The proposed algorithm can effectively solve the path optimization problem in DGT in time.

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